Computer Science Artificial intelligence Course
This course provides a comprehensive introduction to building reliable AI systems for binary classification using tabular data, covering the full pipeline from data preparation to secure deployment.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This course teaches how to develop dependable systems for binary classification using tabular data from the ground up. You will cover data cleaning, preprocessing, feature engineering, and exploratory data analysis, followed by model selection, training, tuning, and evaluation using actual metrics and visual tools. It also includes sourcing datasets, ensuring interpretability, auditing for bias, maintaining privacy, and deploying safely to make AI solutions precise, equitable, and ready for real-world use.
Elevify advantages
Develop skills
- Build clean machine learning datasets by managing imbalances, encoding features, and scaling numerical data.
- Conduct quick exploratory data analysis to identify data leaks, outliers, missing values, and quality problems.
- Train and fine-tune machine learning models using baselines, tree-based ensembles, and optimized hyperparameters.
- Assess AI systems with binary metrics, ROC and PR curves, threshold settings, and SHAP explanations.
- Deploy AI securely by monitoring data drift, checking for bias, and safeguarding user privacy in live environments.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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